Abstract is missing.
- Map Building through Self-Organisation for Robot NavigationUlrich Nehmzow. 1-22 [doi]
- Learning a Navigation Task in Changing Environments by Multi-task Reinforcement LearningAxel Großmann, Riccardo Poli. 23-43 [doi]
- Toward Seamless Transfer from Simulated to Real Worlds: A Dynamically-Rearranging Neural Network ApproachPeter Eggenberger, Akio Ishiguro, Seiji Tokura, Toshiyuki Kondo, Yoshiki Uchikawa. 44-60 [doi]
- How Does a Robot Find Redundancy by Itself?Koh Hosoda, Minoru Asada. 61-70 [doi]
- Learning Robot Control by Relational Concept Induction with Iteratively Controlled ExamplesNobuhiro Inuzuka, Taichi Onda, Hidenori Itoh. 71-83 [doi]
- Reinforcement Learning in Situated Agents: Theoretical and Practical SolutionsMark D. Pendrith. 84-102 [doi]
- A Planning Map for Mobile Robots: Speed Control and Paths Finding in a Changing EnvironmentMathias Quoy, Philippe Gaussier, Sacha Leprêtre, Arnaud Revel, Jean-Paul Banquet. 103-119 [doi]
- Probabilistic and Count Methods in Map Building for Autonomous Mobile RobotsMiguel Rodríguez, José Correa, Roberto Iglesias, Carlos V. Regueiro, Senén Barro. 120-137 [doi]
- Biologically-Inspired Visual Landmark Learning for Mobile RobotsGiovanni M. Bianco, Riccardo Cassinis. 138-164 [doi]